Apple AR/VR heaset
Apple is said to have opted for a standalone AR/VR headset over a more powerful tethered model.
It has had a tumultuous history.
Apple's alleged mixed reality headset appears to be the worst-kept secret in tech, and a fresh story from The Information is jam-packed with details regarding the device's rocky development.
Apple's decision to use a separate headgear is one of the most notable aspects of the story. Apple had yet to determine whether to pursue a more powerful VR headset that would be linked with a base station or a standalone headset. According to The Information, Apple officials chose the standalone product over the version with the base station, which had a processor that later arrived as the M1 Ultra. In 2020, Bloomberg published similar information.
That decision appears to have had a long-term impact on the headset's development. "The device's many processors had already been in development for several years by the time the choice was taken, making it impossible to go back to the drawing board and construct, say, a single chip to handle all the headset's responsibilities," The Information stated. "Other difficulties, such as putting 14 cameras on the headset, have given hardware and algorithm engineers stress."
Jony Ive remained to consult on the project's design even after his official departure from Apple, according to the story. Ive "prefers" a wearable battery, such as that offered by Magic Leap. Other prototypes, according to The Information, placed the battery in the headset's headband, and it's unknown which will be used in the final design.
The headset was purportedly shown to Apple's board of directors last week, indicating that a public unveiling is imminent. However, it is possible that it will not be introduced until later this year, and it may not hit shop shelves until 2023, so we may have to wait a bit to try it.
For further down the line, Apple is working on a pair of AR spectacles that appear like Ray-Ban wayfarer sunglasses, but according to The Information, they're "still several years away from release." (I'm interested to see how they compare to Meta and Ray-Bans' true wayfarer-style glasses.)
More on Technology

Amelia Winger-Bearskin
3 years ago
Reasons Why AI-Generated Images Remind Me of Nightmares
AI images are like funhouse mirrors.
Google's AI Blog introduced the puppy-slug in the summer of 2015.
Puppy-slug isn't a single image or character. "Puppy-slug" refers to Google's DeepDream's unsettling psychedelia. This tool uses convolutional neural networks to train models to recognize dataset entities. If researchers feed the model millions of dog pictures, the network will learn to recognize a dog.
DeepDream used neural networks to analyze and classify image data as well as generate its own images. DeepDream's early examples were created by training a convolutional network on dog images and asking it to add "dog-ness" to other images. The models analyzed images to find dog-like pixels and modified surrounding pixels to highlight them.
Puppy-slugs and other DeepDream images are ugly. Even when they don't trigger my trypophobia, they give me vertigo when my mind tries to reconcile familiar features and forms in unnatural, physically impossible arrangements. I feel like I've been poisoned by a forbidden mushroom or a noxious toad. I'm a Lovecraft character going mad from extradimensional exposure. They're gross!
Is this really how AIs see the world? This is possibly an even more unsettling topic that DeepDream raises than the blatant abjection of the images.
When these photographs originally circulated online, many friends were startled and scandalized. People imagined a computer's imagination would be literal, accurate, and boring. We didn't expect vivid hallucinations and organic-looking formations.
DeepDream's images didn't really show the machines' imaginations, at least not in the way that scared some people. DeepDream displays data visualizations. DeepDream reveals the "black box" of convolutional network training.
Some of these images look scary because the models don't "know" anything, at least not in the way we do.
These images are the result of advanced algorithms and calculators that compare pixel values. They can spot and reproduce trends from training data, but can't interpret it. If so, they'd know dogs have two eyes and one face per head. If machines can think creatively, they're keeping it quiet.
You could be forgiven for thinking otherwise, given OpenAI's Dall-impressive E's results. From a technological perspective, it's incredible.
Arthur C. Clarke once said, "Any sufficiently advanced technology is indistinguishable from magic." Dall-magic E's requires a lot of math, computer science, processing power, and research. OpenAI did a great job, and we should applaud them.
Dall-E and similar tools match words and phrases to image data to train generative models. Matching text to images requires sorting and defining the images. Untold millions of low-wage data entry workers, content creators optimizing images for SEO, and anyone who has used a Captcha to access a website make these decisions. These people could live and die without receiving credit for their work, even though the project wouldn't exist without them.
This technique produces images that are less like paintings and more like mirrors that reflect our own beliefs and ideals back at us, albeit via a very complex prism. Due to the limitations and biases that these models portray, we must exercise caution when viewing these images.
The issue was succinctly articulated by artist Mimi Onuoha in her piece "On Algorithmic Violence":
As we continue to see the rise of algorithms being used for civic, social, and cultural decision-making, it becomes that much more important that we name the reality that we are seeing. Not because it is exceptional, but because it is ubiquitous. Not because it creates new inequities, but because it has the power to cloak and amplify existing ones. Not because it is on the horizon, but because it is already here.

Nicolas Tresegnie
3 years ago
Launching 10 SaaS applications in 100 days
Apocodes helps entrepreneurs create SaaS products without writing code. This post introduces micro-SaaS and outlines its basic strategy.
Strategy
Vision and strategy differ when starting a startup.
The company's long-term future state is outlined in the vision. It establishes the overarching objectives the organization aims to achieve while also justifying its existence. The company's future is outlined in the vision.
The strategy consists of a collection of short- to mid-term objectives, the accomplishment of which will move the business closer to its vision. The company gets there through its strategy.
The vision should be stable, but the strategy must be adjusted based on customer input, market conditions, or previous experiments.
Begin modestly and aim high.
Be truthful. It's impossible to automate SaaS product creation from scratch. It's like climbing Everest without running a 5K. Physical rules don't prohibit it, but it would be suicide.
Apocodes 5K equivalent? Two options:
(A) Create a feature that includes every setting option conceivable. then query potential clients “Would you choose us to build your SaaS solution if we offered 99 additional features of the same caliber?” After that, decide which major feature to implement next.
(B) Build a few straightforward features with just one or two configuration options. Then query potential clients “Will this suffice to make your product?” What's missing if not? Finally, tweak the final result a bit before starting over.
(A) is an all-or-nothing approach. It's like training your left arm to climb Mount Everest. My right foot is next.
(B) is a better method because it's iterative and provides value to customers throughout.
Focus on a small market sector, meet its needs, and expand gradually. Micro-SaaS is Apocode's first market.
What is micro-SaaS.
Micro-SaaS enterprises have these characteristics:
A limited range: They address a specific problem with a small number of features.
A small group of one to five individuals.
Low external funding: The majority of micro-SaaS companies have Total Addressable Markets (TAM) under $100 million. Investors find them unattractive as a result. As a result, the majority of micro-SaaS companies are self-funded or bootstrapped.
Low competition: Because they solve problems that larger firms would rather not spend time on, micro-SaaS enterprises have little rivalry.
Low upkeep: Because of their simplicity, they require little care.
Huge profitability: Because providing more clients incurs such a small incremental cost, high profit margins are possible.
Micro-SaaS enterprises created with no-code are Apocode's ideal first market niche.
We'll create our own micro-SaaS solutions to better understand their needs. Although not required, we believe this will improve community discussions.
The challenge
In 100 days (September 12–December 20, 2022), we plan to build 10 micro-SaaS enterprises using Apocode.
They will be:
Self-serve: Customers will be able to use the entire product experience without our manual assistance.
Real: They'll deal with actual issues. They won't be isolated proofs of concept because we'll keep up with them after the challenge.
Both free and paid options: including a free plan and a free trial period. Although financial success would be a good result, the challenge's stated objective is not financial success.
This will let us design Apocodes features, showcase them, and talk to customers.
(Edit: The first micro-SaaS was launched!)
Follow along
If you want to follow the story of Apocode or our progress in this challenge, you can subscribe here.
If you are interested in using Apocode, sign up here.
If you want to provide feedback, discuss the idea further or get involved, email me at nicolas.tresegnie@gmail.com

Gajus Kuizinas
3 years ago
How a few lines of code were able to eliminate a few million queries from the database
I was entering tens of millions of records per hour when I first published Slonik PostgreSQL client for Node.js. The data being entered was usually flat, making it straightforward to use INSERT INTO ... SELECT * FROM unnset() pattern. I advocated the unnest approach for inserting rows in groups (that was part I).
However, today I’ve found a better way: jsonb_to_recordset.
jsonb_to_recordsetexpands the top-level JSON array of objects to a set of rows having the composite type defined by an AS clause.
jsonb_to_recordset allows us to query and insert records from arbitrary JSON, like unnest. Since we're giving JSON to PostgreSQL instead of unnest, the final format is more expressive and powerful.
SELECT *
FROM json_to_recordset('[{"name":"John","tags":["foo","bar"]},{"name":"Jane","tags":["baz"]}]')
AS t1(name text, tags text[]);
name | tags
------+-----------
John | {foo,bar}
Jane | {baz}
(2 rows)Let’s demonstrate how you would use it to insert data.
Inserting data using json_to_recordset
Say you need to insert a list of people with attributes into the database.
const persons = [
{
name: 'John',
tags: ['foo', 'bar']
},
{
name: 'Jane',
tags: ['baz']
}
];You may be tempted to traverse through the array and insert each record separately, e.g.
for (const person of persons) {
await pool.query(sql`
INSERT INTO person (name, tags)
VALUES (
${person.name},
${sql.array(person.tags, 'text[]')}
)
`);
}It's easier to read and grasp when working with a few records. If you're like me and troubleshoot a 2M+ insert query per day, batching inserts may be beneficial.
What prompted the search for better alternatives.
Inserting using unnest pattern might look like this:
await pool.query(sql`
INSERT INTO public.person (name, tags)
SELECT t1.name, t1.tags::text[]
FROM unnest(
${sql.array(['John', 'Jane'], 'text')},
${sql.array(['{foo,bar}', '{baz}'], 'text')}
) AS t1.(name, tags);
`);You must convert arrays into PostgreSQL array strings and provide them as text arguments, which is unsightly. Iterating the array to create slices for each column is likewise unattractive.
However, with jsonb_to_recordset, we can:
await pool.query(sql`
INSERT INTO person (name, tags)
SELECT *
FROM jsonb_to_recordset(${sql.jsonb(persons)}) AS t(name text, tags text[])
`);In contrast to the unnest approach, using jsonb_to_recordset we can easily insert complex nested data structures, and we can pass the original JSON document to the query without needing to manipulate it.
In terms of performance they are also exactly the same. As such, my current recommendation is to prefer jsonb_to_recordset whenever inserting lots of rows or nested data structures.
You might also like

obimy.app
3 years ago
How TikTok helped us grow to 6 million users
This resulted to obimy's new audience.
Hi! obimy's official account. Here, we'll teach app developers and marketers. In 2022, our downloads increased dramatically, so we'll share what we learned.
obimy is what we call a ‘senseger’. It's a new method to communicate digitally. Instead of text, obimy users connect through senses and moods. Feeling playful? Flirt with your partner, pat a pal, or dump water on a classmate. Each feeling is an interactive animation with vibration. It's a wordless app. App Store and Google Play have obimy.
We had 20,000 users in 2022. Two to five thousand of them opened the app monthly. Our DAU metric was 500.
We have 6 million users after 6 months. 500,000 individuals use obimy daily. obimy was the top lifestyle app this week in the U.S.
And TikTok helped.
TikTok fuels obimys' growth. It's why our app exploded. How and what did we learn? Our Head of Marketing, Anastasia Avramenko, knows.
our actions prior to TikTok
We wanted to achieve product-market fit through organic expansion. Quora, Reddit, Facebook Groups, Facebook Ads, Google Ads, Apple Search Ads, and social media activity were tested. Nothing worked. Our CPI was sometimes $4, so unit economics didn't work.
We studied our markets and made audience hypotheses. We promoted our goods and studied our audience through social media quizzes. Our target demographic was Americans in long-distance relationships. I designed quizzes like Test the Strength of Your Relationship to better understand the user base. After each quiz, we encouraged users to download the app to enhance their connection and bridge the distance.
We got 1,000 responses for $50. This helped us comprehend the audience's grief and coping strategies (aka our rivals). I based action items on answers given. If you can't embrace a loved one, use obimy.
We also tried Facebook and Google ads. From the start, we knew it wouldn't work.
We were desperate to discover a free way to get more users.
Our journey to TikTok
TikTok is a great venue for emerging creators. It also helped reach people. Before obimy, my TikTok videos garnered 12 million views without sponsored promotion.
We had to act. TikTok was required.
I wasn't a TikTok user before obimy. Initially, I uploaded promotional content. Call-to-actions appear strange next to dancing challenges and my money don't jiggle jiggle. I learned TikTok. Watch TikTok for an hour was on my to-do list. What a dream job!
Our most popular movies presented the app alongside text outlining what it does. We started promoting them in Europe and the U.S. and got a 16% CTR and $1 CPI, an improvement over our previous efforts.
Somehow, we were expanding. So we came up with new hypotheses, calls to action, and content.
Four months passed, yet we saw no organic growth.
Russia attacked Ukraine.
Our app aimed to be helpful. For now, we're focusing on our Ukrainian audience. I posted sloppy TikToks illustrating how obimy can help during shelling or air raids.
In two hours, Kostia sent me our visitor count. Our servers crashed.
Initially, we had several thousand daily users. Over 200,000 users joined obimy in a week. They posted obimy videos on TikTok, drawing additional users. We've also resumed U.S. video promotion.
We gained 2,000,000 new members with less than $100 in ads, primarily in the U.S. and U.K.
TikTok helped.
The figures
We were confident we'd chosen the ideal tool for organic growth.
Over 45 million people have viewed our own videos plus a ton of user-generated content with the hashtag #obimy.
About 375 thousand people have liked all of our individual videos.
The number of downloads and the virality of videos are directly correlated.
Where are we now?
TikTok fuels our organic growth. We post 56 videos every week and pay to promote viral content.
We use UGC and influencers. We worked with Universal Music Italy on Eurovision. They offered to promote us through their million-follower TikTok influencers. We thought their followers would improve our audience, but it didn't matter. Integration didn't help us. Users that share obimy videos with their followers can reach several million views, which affects our download rate.
After the dust settled, we determined our key audience was 13-18-year-olds. They want to express themselves, but it's sometimes difficult. We're searching for methods to better engage with our users. We opened a Discord server to discuss anime and video games and gather app and content feedback.
TikTok helps us test product updates and hypotheses. Example: I once thought we might raise MAU by prompting users to add strangers as friends. Instead of asking our team to construct it, I made a TikTok urging users to share invite URLs. Users share links under every video we upload, embracing people worldwide.
Key lessons
Don't direct-sell. TikTok isn't for Instagram, Facebook, or YouTube promo videos. Conventional advertisements don't fit. Most users will swipe up and watch humorous doggos.
More product videos are better. Finally. So what?
Encourage interaction. Tagging friends in comments or making videos with the app promotes it more than any marketing spend.
Be odd and risqué. A user mistakenly sent a French kiss to their mom in one of our most popular videos.
TikTok helps test hypotheses and build your user base. It also helps develop apps. In our upcoming blog, we'll guide you through obimy's design revisions based on TikTok. Follow us on Twitter, Instagram, and TikTok.

Nitin Sharma
2 years ago
Web3 Terminology You Should Know
The easiest online explanation.
Web3 is growing. Crypto companies are growing.
Instagram, Adidas, and Stripe adopted cryptocurrency.
Bitcoin and other cryptocurrencies made web3 famous.
Most don't know where to start. Cryptocurrency, DeFi, etc. are investments.
Since we don't understand web3, I'll help you today.
Let’s go.
1. Web3
It is the third generation of the web, and it is built on the decentralization idea which means no one can control it.
There are static webpages that we can only read on the first generation of the web (i.e. Web 1.0).
Web 2.0 websites are interactive. Twitter, Medium, and YouTube.
Each generation controlled the website owner. Simply put, the owner can block us. However, data breaches and selling user data to other companies are issues.
They can influence the audience's mind since they have control.
Assume Twitter's CEO endorses Donald Trump. Result? Twitter would have promoted Donald Trump with tweets and graphics, enhancing his chances of winning.
We need a decentralized, uncontrollable system.
And then there’s Web3.0 to consider. As Bitcoin and Ethereum values climb, so has its popularity. Web3.0 is uncontrolled web evolution. It's good and bad.
Dapps, DeFi, and DAOs are here. It'll all be explained afterwards.
2. Cryptocurrencies:
No need to elaborate.
Bitcoin, Ethereum, Cardano, and Dogecoin are cryptocurrencies. It's digital money used for payments and other uses.
Programs must interact with cryptocurrencies.
3. Blockchain:
Blockchain facilitates bitcoin transactions, investments, and earnings.
This technology governs Web3. It underpins the web3 environment.
Let us delve much deeper.
Blockchain is simple. However, the name expresses the meaning.
Blockchain is a chain of blocks.
Let's use an image if you don't understand.
The graphic above explains blockchain. Think Blockchain. The block stores related data.
Here's more.
4. Smart contracts
Programmers and developers must write programs. Smart contracts are these blockchain apps.
That’s reasonable.
Decentralized web3.0 requires immutable smart contracts or programs.
5. NFTs
Blockchain art is NFT. Non-Fungible Tokens.
Explaining Non-Fungible Token may help.
Two sorts of tokens:
These tokens are fungible, meaning they can be changed. Think of Bitcoin or cash. The token won't change if you sell one Bitcoin and acquire another.
Non-Fungible Token: Since these tokens cannot be exchanged, they are exclusive. For instance, music, painting, and so forth.
Right now, Companies and even individuals are currently developing worthless NFTs.
The concept of NFTs is much improved when properly handled.
6. Dapp
Decentralized apps are Dapps. Instagram, Twitter, and Medium apps in the same way that there is a lot of decentralized blockchain app.
Curve, Yearn Finance, OpenSea, Axie Infinity, etc. are dapps.
7. DAOs
DAOs are member-owned and governed.
Consider it a company with a core group of contributors.
8. DeFi
We all utilize centrally regulated financial services. We fund these banks.
If you have $10,000 in your bank account, the bank can invest it and retain the majority of the profits.
We only get a penny back. Some banks offer poor returns. To secure a loan, we must trust the bank, divulge our information, and fill out lots of paperwork.
DeFi was built for such issues.
Decentralized banks are uncontrolled. Staking, liquidity, yield farming, and more can earn you money.
Web3 beginners should start with these resources.

Jeff Scallop
2 years ago
The Age of Decentralized Capitalism and DeFi
DeCap is DeFi's killer app.
“Software is eating the world.” Marc Andreesen, venture capitalist
DeFi. Imagine a blockchain-based alternative financial system that offers the same products and services as traditional finance, but with more variety, faster, more secure, lower cost, and simpler access.
Decentralised finance (DeFi) is a marketplace without gatekeepers or central authority managing the flow of money, where customers engage directly with smart contracts running on a blockchain.
DeFi grew exponentially in 2020/21, with Total Value Locked (an inadequate estimate for market size) topping at $100 billion. After that, it crashed.
The accumulation of funds by individuals with high discretionary income during the epidemic, the novelty of crypto trading, and the high yields given (5% APY for stablecoins on established platforms to 100%+ for risky assets) are among the primary elements explaining this exponential increase.
No longer your older brothers DeFi
Since transactions are anonymous, borrowers had to overcollateralize DeFi 1.0. To borrow $100 in stablecoins, you must deposit $150 in ETH. DeFi 1.0's business strategy raises two problems.
Why does DeFi offer interest rates that are higher than those of the conventional financial system?;
Why would somebody put down more cash than they intended to borrow?
Maxed out on their own resources, investors took loans to acquire more crypto; the demand for those loans raised DeFi yields, which kept crypto prices increasing; as crypto prices rose, investors made a return on their positions, allowing them to deposit more money and borrow more crypto.
This is a bull market game. DeFi 1.0's overcollateralization speculation is dead. Cryptocrash sank it.
The “speculation by overcollateralisation” world of DeFi 1.0 is dead
At a JP Morgan digital assets conference, institutional investors were more interested in DeFi than crypto or fintech. To me, that shows DeFi 2.0's institutional future.
DeFi 2.0 protocols must handle KYC/AML, tax compliance, market abuse, and cybersecurity problems to be institutional-ready.
Stablecoins gaining market share under benign regulation and more CBDCs coming online in the next couple of years could help DeFi 2.0 separate from crypto volatility.
DeFi 2.0 will have a better footing to finally decouple from crypto volatility
Then we can transition from speculation through overcollateralization to DeFi's genuine comparative advantages: cheaper transaction costs, near-instant settlement, more efficient price discovery, faster time-to-market for financial innovation, and a superior audit trail.
Akin to Amazon for financial goods
Amazon decimated brick-and-mortar shops by offering millions of things online, warehouses by keeping just-in-time inventory, and back-offices by automating invoicing and payments. Software devoured retail. DeFi will eat banking with software.
DeFi is the Amazon for financial items that will replace fintech. Even the most advanced internet brokers offer only 100 currency pairings and limited bonds, equities, and ETFs.
Old banks settlement systems and inefficient, hard-to-upgrade outdated software harm them. For advanced gamers, it's like driving an F1 vehicle on dirt.
It is like driving a F1 car on a dirt road, for the most sophisticated players
Central bankers throughout the world know how expensive and difficult it is to handle cross-border payments using the US dollar as the reserve currency, which is vulnerable to the economic cycle and geopolitical tensions.
Decentralization is the only method to deliver 24h global financial markets. DeFi 2.0 lets you buy and sell startup shares like Google or Tesla. VC funds will trade like mutual funds. Or create a bundle coverage for your car, house, and NFTs. Defi 2.0 consumes banking and creates Global Wall Street.
Defi 2.0 is how software eats banking and delivers the global Wall Street
Decentralized Capitalism is Emerging
90% of markets are digital. 10% is hardest to digitalize. That's money creation, ID, and asset tokenization.
90% of financial markets are already digital. The only problem is that the 10% left is the hardest to digitalize
Debt helped Athens construct a powerful navy that secured trade routes. Bonds financed the Renaissance's wars and supply chains. Equity fueled industrial growth. FX drove globalization's payments system. DeFi's plans:
If the 20th century was a conflict between governments and markets over economic drivers, the 21st century will be between centralized and decentralized corporate structures.
Offices vs. telecommuting. China vs. onshoring/friendshoring. Oil & gas vs. diverse energy matrix. National vs. multilateral policymaking. DAOs vs. corporations Fiat vs. crypto. TradFi vs.
An age where the network effects of the sharing economy will overtake the gains of scale of the monopolistic competition economy
This is the dawn of Decentralized Capitalism (or DeCap), an age where the network effects of the sharing economy will reach a tipping point and surpass the scale gains of the monopolistic competition economy, further eliminating inefficiencies and creating a more robust economy through better data and automation. DeFi 2.0 enables this.
DeFi needs to pay the piper now.
DeCap won't be Web3.0's Shangri-La, though. That's too much for an ailing Atlas. When push comes to shove, DeFi folks want to survive and fight another day for the revolution. If feasible, make a tidy profit.
Decentralization wasn't meant to circumvent regulation. It circumvents censorship. On-ramp, off-ramp measures (control DeFi's entry and exit points, not what happens in between) sound like a good compromise for DeFi 2.0.
The sooner authorities realize that DeFi regulation is made ex-ante by writing code and constructing smart contracts with rules, the faster DeFi 2.0 will become the more efficient and safe financial marketplace.
More crucially, we must boost system liquidity. DeFi's financial stability risks are downplayed. DeFi must improve its liquidity management if it's to become mainstream, just as banks rely on capital constraints.
This reveals the complex and, frankly, inadequate governance arrangements for DeFi protocols. They redistribute control from tokenholders to developers, which is bad governance regardless of the economic model.
But crypto can only ride the existing banking system for so long before forming its own economy. DeFi will upgrade web2.0's financial rails till then.
